A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning
J. Kneifl, D. Grunert, and J. Fehr. International Journal for Numerical Methods in Engineering, (April 2021)initial preprint available under http://elib.uni-stuttgart.de/handle/11682/11198.
DOI: 10.1002/nme.6712
%0 Journal Article
%1 KneiflGrunertFehr2021
%A Kneifl, Jonas
%A Grunert, Dennis
%A Fehr, Joerg
%D 2021
%I Wiley
%J International Journal for Numerical Methods in Engineering
%K PN7 PN7-6 EXC2075 selected
%R 10.1002/nme.6712
%T A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning
%U https://doi.org/10.1002%2Fnme.6712
@article{KneiflGrunertFehr2021,
added-at = {2024-03-26T11:56:32.000+0100},
author = {Kneifl, Jonas and Grunert, Dennis and Fehr, Joerg},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2c6c53d5c369ab742722817452d6f3909/exc2075},
doi = {10.1002/nme.6712},
interhash = {ebff56638151df73a7826c0567b8089b},
intrahash = {c6c53d5c369ab742722817452d6f3909},
journal = {International Journal for Numerical Methods in Engineering},
keywords = {PN7 PN7-6 EXC2075 selected},
month = {04},
note = {initial preprint available under http://elib.uni-stuttgart.de/handle/11682/11198},
publisher = {Wiley},
timestamp = {2024-03-26T11:56:32.000+0100},
title = {A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning},
url = {https://doi.org/10.1002%2Fnme.6712},
year = 2021
}